Introduction

This report shows latest metrics for App A and App B. Both apps are dummy examples and all values, comments, and conclusions exposed here are completely fake. The unique purpose of this is to show an example of a reproducible report designed and built end-to-end in R.

As non-expert in App analytics, I based this analysis on the Apple’s App Analytics, an Apple Developer tool for measure app’s performance.

Overview

Active User Metrics

A

50M

Daily Active Users (DAU)

1.5B

Monthly Active Users (MAU)

B

80M

Daily Active Users (DAU)

2.4B

Monthly Active Users (MAU)

App Metrics

Latest metrics for app A and B

App A

223 impressions
346 product page view
2578 conversion rate
2338 total downloads
2704 proceeds
4336 sessions

App B

2446 impressions
2692 product page view
7156 conversion rate
6676 total downloads
7408 proceeds
10672 sessions

Messages

Crashes increase 20% in App A

Crashes increase 10% in App B

App profiles

Top 10 Feature’s Profiles of app A and B

App Profiles

Radar chart shows the app's profile by feature. Each point represents the average percentage of time a user spend on this app feature.

Conclusions

Regarding conversion rates and number of impressions, App B demonstrates to be better option for the next campaign.

Please note that all values, comments and conclusions stated in this report are entirely fake and only purpose is to show an example of reproducible report design and build end-to-end in R.